With the latest release of the CUDA parallel programming model, we’ve made improvements in all these areas.

Available now to all developers on the CUDA website, the CUDA 6 Release Candidate is packed with several new features that are sure to please developers.

A few highlights:

Unified Memory – This major new feature lets CUDA applications access CPU and GPU memory without the need to manually copy data from one to the other. This is a major time saver that simplifies the programming process, and makes it easier for programmers to add GPU acceleration in a wider range of applications.

Drop-in Libraries – Want to instantly accelerate your application by up to 8X? The new drop-in libraries can automatically accelerate your BLAS and FFTW calculations by simply replacing the existing CPU-only BLAS or FFTW library with the new, GPU-accelerated equivalent.

Multi-GPU Scaling – Re-designed BLAS and FFT GPU libraries automatically scale performance across up to eight GPUs in a single node. This provides over nine teraflops of double-precision performance per node, supporting larger workloads than ever before (up to 512GB).

And there’s more.

In addition to the new features, the CUDA 6 platform offers a full suite of programming tools, GPU-accelerated math libraries, documentation and programming guides.

To keep informed about the latest CUDA developments, and to access a range parallel programing tools and resources, we encourage you to sign up for the free CUDA/GPU Computing Registered Developer Program at the NVIDIA Developer Zone website